DOI: 10.1093/biomet/asad080 ISSN: 0006-3444

Central limit theorems for local network statistics

P A Maugis
  • Applied Mathematics
  • Statistics, Probability and Uncertainty
  • General Agricultural and Biological Sciences
  • Agricultural and Biological Sciences (miscellaneous)
  • General Mathematics
  • Statistics and Probability


Subgraph counts, in particular the number of occurrences of small shapes such as triangles, characterize properties of random networks. As a result, they have seen wide use as network summary statistics. Subgraphs are typically counted globally, making existing approaches unable to describe vertex-specific characteristics. In contrast, rooted subgraphs focus on vertex neighbourhoods, and are fundamental descriptors of local network properties. We derive the asymptotic joint distribution of rooted subgraph counts in inhomogeneous random graphs, a model which generalizes most statistical network models. This result enables a shift in the statistical analysis of graphs, from estimating network summaries, to estimating models linking local network structure and vertex-specific covariates. As an example, we consider a school friendship network and show that gender and race are significant predictors of local friendship patterns.

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